Three-dimensional scene reconstruction and Kalman filter

Artyom Makovetskii; Sergei Voronin; Vitaly Kober; Aleksei Voronin; Tatyana Makovetskaya

doi:10.1117/12.3027867

30 September 2024 Three-dimensional scene reconstruction and Kalman filter

Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin, Tatyana Makovetskaya

Proceedings Volume 13137, Applications of Digital Image Processing XLVII; 131371D (2024) https://doi.org/10.1117/12.3027867
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Conference Poster

Abstract

Simultaneous Localization and Mapping (SLAM) is the task of reconstructing an environmental model passed using onboard sensors and at the same time maintaining an estimate of the mobile sensor location within the model. One of the known approaches to the SLAM problem is the Kalman filter. The Kalman filter efficiency is based on the fact that it contains a fully correlated posterior over feature maps and mobile sensor poses. The important element of the SLAM problem is the reconstruction of the environmental 3D scene. In this paper, we propose an algorithm to restore the 3D scene using consistent condition and a modified version of the Kalman filter. The reconstruction algorithm is noniterative. Computer simulation results are provided to illustrate the performance of the proposed method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin, and Tatyana Makovetskaya "Three-dimensional scene reconstruction and Kalman filter", Proc. SPIE 13137, Applications of Digital Image Processing XLVII, 131371D (30 September 2024); https://doi.org/10.1117/12.3027867

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